Adaptive application logger

ABSTRACT

Embodiments of the invention provide systems and methods for logging of messages in a development environment. More specifically, embodiments of the present invention provide dynamically adaptive logging of runtime messages generated by an application. These embodiments provide a way to handle the volume of information stored in the logs by dynamically changing the severity associated with generated messages based on previous code path execution. Embodiments can use a set of metrics to replace the usual static log level associated with the code by the developer. For example, such metrics can include but are not limited to a cost-based (storage volume on disk), an exception-based (weight increase in catch block), and/or a crowd-based (community can vote down noise). As a result, embodiments can provide more detailed information when the error is recurring for a particular user but without generating so much information as to make the log difficult to use.

BACKGROUND OF THE INVENTION

Embodiments of the present invention relate generally to methods andsystems for logging of messages in a development environment and moreparticularly to providing dynamically adaptive logging of runtimemessages generated by an application.

Logging refers to the generation of messages and the recording ofactivity based on those messages. A logging framework is commonly usedin a development environment by developers of an application under test.In a logging framework, a logger application or object allows theapplication under development to log messages generated during executionof that application in the development environment. For example, theapplication can log a message by passing an object or an exceptionhaving a particular severity level to the logging framework. The loggerof the framework can log a message associated with the object orexception which can then be used by the developers to trace execution ofthe application in an effort to debug the application. Current loggingframeworks, such as the Java logging framework for example, are based ona static log level associated with the specific object or exception. Forexample, these levels can be defined in terms of severity such as“trace,” “debug,” “info,” “warning,” “error,” and “fatal” to indicateincreasing degrees of how serious a message should be considered. Theselevels are associated with the code by the code developer at designtime. The logger framework can be configured by the developer to logthose messages generated at or above a particular severity level.

However, the static definition of a log level in such an approach canpresent some difficulties for the developers. For example, if theseverity level is set too high, the developer may not be able to findenough information in the logs to effectively find a root cause of aproblem or to otherwise troubleshoot a problem. To correct this, thedeveloper needs to change the setup or configuration of the loggingframework to capture the information needed, e.g., to change theseverity level of messages logged. This may, in many cases, require thesystem to be restarted. Then, if the severity level is too low, the logsmay be flooded with such a volume of messages that the developer canhave a difficult, if not impossible, task of finding a relevant messagein the resulting logs. Hence, there is a need for improved methods andsystems for logging of messages in a development environment.

BRIEF SUMMARY OF THE INVENTION

Embodiments of the invention provide systems and methods for providingdynamically adaptive logging of runtime messages generated by anapplication. According to one embodiment, adaptively logging runtimemessages related to an application can comprise detecting a predefinedcondition of the application and determining an execution state of theapplication at a time the predefined condition is detected. Adetermination can be made dynamically as to whether to generate a logmessage associated with the detected predefined condition or to suppressgeneration of the log message associated with the detected predefinedcondition based at least in part on the determined execution state atthe time the predefined condition is detected.

Dynamically determining whether to generate a log message associatedwith the detected predefined condition or to suppress generation of thelog message associated with the detected predefined condition cancomprise determining whether the predefined condition has beenpreviously detected. In response to determining the predefined conditionhas not been previously detected, generation of the log messageassociated with the detected predefined condition can be suppressed, thedetected predefined condition and the determined execution state of theapplication at a time the predefined condition is detected can be saved,and the detected predefined condition can be weighted.

In response to determining the predefined condition has been previouslydetected, a further determination can be made, based on a set of one ormore metrics, as to whether to generate a log message associated withthe detected predefined condition or to suppress generation of the logmessage associated with the detected predefined condition. For example,the metrics can comprise one or more cost-based metrics, one or moreexception-based metrics, and/or other metrics. In response todetermining to suppress generation of the log message associated withthe detected predefined condition based on a set of one or more metrics,generation of the log message associated with the detected predefinedcondition can be suppressed and the weight of the detected predefinedcondition can be increased. In response to determining to generate thelog message associated with the detected predefined condition based on aset of one or more metrics, the weight of the detected predefinedcondition can be increased and the log message associated with thedetected predefined condition can be generated.

A determination can be made as to whether to continue adaptively loggingruntime messages associated with the detected predefined condition ofthe application. In response to determining to not continue adaptivelylogging runtime messages associated with the detected predefinedcondition for the application, logging of messages associated with thedetected predefined condition and for the determined execution state ofthe application can be halted.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram illustrating components of an exemplarydistributed system in which various embodiments of the present inventionmay be implemented.

FIG. 2 is a block diagram illustrating components of a systemenvironment by which services provided by embodiments of the presentinvention may be offered as cloud services.

FIG. 3 is a block diagram illustrating an exemplary computer system inwhich embodiments of the present invention may be implemented.

FIG. 4 is a block diagram illustrating, at a high-level, functionalcomponents of a system for providing dynamically adaptive logging ofruntime messages generated by an application according to one embodimentof the present invention.

FIG. 5 is a flowchart illustrating a process for providing dynamicallyadaptive logging of runtime messages generated by an applicationaccording to one embodiment of the present invention.

DETAILED DESCRIPTION OF THE INVENTION

In the following description, for the purposes of explanation, numerousspecific details are set forth in order to provide a thoroughunderstanding of various embodiments of the present invention. It willbe apparent, however, to one skilled in the art that embodiments of thepresent invention may be practiced without some of these specificdetails. In other instances, well-known structures and devices are shownin block diagram form.

The ensuing description provides exemplary embodiments only, and is notintended to limit the scope, applicability, or configuration of thedisclosure. Rather, the ensuing description of the exemplary embodimentswill provide those skilled in the art with an enabling description forimplementing an exemplary embodiment. It should be understood thatvarious changes may be made in the function and arrangement of elementswithout departing from the spirit and scope of the invention as setforth in the appended claims.

Specific details are given in the following description to provide athorough understanding of the embodiments. However, it will beunderstood by one of ordinary skill in the art that the embodiments maybe practiced without these specific details. For example, circuits,systems, networks, processes, and other components may be shown ascomponents in block diagram form in order not to obscure the embodimentsin unnecessary detail. In other instances, well-known circuits,processes, algorithms, structures, and techniques may be shown withoutunnecessary detail in order to avoid obscuring the embodiments.

Also, it is noted that individual embodiments may be described as aprocess which is depicted as a flowchart, a flow diagram, a data flowdiagram, a structure diagram, or a block diagram. Although a flowchartmay describe the operations as a sequential process, many of theoperations can be performed in parallel or concurrently. In addition,the order of the operations may be re-arranged. A process is terminatedwhen its operations are completed, but could have additional steps notincluded in a figure. A process may correspond to a method, a function,a procedure, a subroutine, a subprogram, etc. When a process correspondsto a function, its termination can correspond to a return of thefunction to the calling function or the main function.

The term “machine-readable medium” includes, but is not limited toportable or fixed storage devices, optical storage devices, and variousother mediums capable of storing, containing or carrying instruction(s)and/or data. A code segment or machine-executable instructions mayrepresent a procedure, a function, a subprogram, a program, a routine, asubroutine, a module, a software package, a class, or any combination ofinstructions, data structures, or program statements. A code segment maybe coupled to another code segment or a hardware circuit by passingand/or receiving information, data, arguments, parameters, or memorycontents. Information, arguments, parameters, data, etc. may be passed,forwarded, or transmitted via any suitable means including memorysharing, message passing, token passing, network transmission, etc.

Furthermore, embodiments may be implemented by hardware, software,firmware, middleware, microcode, hardware description languages, or anycombination thereof. When implemented in software, firmware, middlewareor microcode, the program code or code segments to perform the necessarytasks may be stored in a machine readable medium. A processor(s) mayperform the necessary tasks.

Embodiments of the invention provide systems and methods for logging ofmessages in a development environment. More specifically, embodiments ofthe present invention provide dynamically adaptive logging of runtimemessages generated by an application. These embodiments provide a way tohandle the volume of information stored in the logs by dynamicallychanging the severity associated with generated messages based onprevious code path execution. Additionally or alternatively, embodimentscan use a set of metrics to replace the usual static log levelassociated with the code by the developer. For example, such metrics caninclude but are not limited to a cost-based (storage volume on disk), anexception-based (weight increase in catch block), and/or a crowd-based(community can vote down noise). As a result, embodiments can providemore detailed information when the error is recurring for a particularuser but without generating so much information as to make the logdifficult to use. Various additional details of embodiments of thepresent invention will be described below with reference to the figures.

FIG. 1 is a block diagram illustrating components of an exemplarydistributed system in which various embodiments of the present inventionmay be implemented. In the illustrated embodiment, distributed system100 includes one or more client computing devices 102, 104, 106, and108, which are configured to execute and operate a client applicationsuch as a web browser, proprietary client (e.g., Oracle Forms), or thelike over one or more network(s) 110. Server 112 may be communicativelycoupled with remote client computing devices 102, 104, 106, and 108 vianetwork 110.

In various embodiments, server 112 may be adapted to run one or moreservices or software applications provided by one or more of thecomponents of the system. In some embodiments, these services may beoffered as web-based or cloud services or under a Software as a Service(SaaS) model to the users of client computing devices 102, 104, 106,and/or 108. Users operating client computing devices 102, 104, 106,and/or 108 may in turn utilize one or more client applications tointeract with server 112 to utilize the services provided by thesecomponents.

In the configuration depicted in the figure, the software components118, 120 and 122 of system 100 are shown as being implemented on server112. In other embodiments, one or more of the components of system 100and/or the services provided by these components may also be implementedby one or more of the client computing devices 102, 104, 106, and/or108. Users operating the client computing devices may then utilize oneor more client applications to use the services provided by thesecomponents. These components may be implemented in hardware, firmware,software, or combinations thereof. It should be appreciated thatdifferent system configurations are possible, which may be differentfrom distributed system 100. The embodiment shown in the figure is thusone example of a distributed system for implementing an embodimentsystem and is not intended to be limiting.

Client computing devices 102, 104, 106, and/or 108 may be portablehandheld devices (e.g., an iPhone®, cellular telephone, an iPad®,computing tablet, a personal digital assistant (PDA)) or wearabledevices (e.g., a Google Glass® head mounted display), running softwaresuch as Microsoft Windows Mobile®, and/or a variety of mobile operatingsystems such as iOS, Windows Phone, Android, BlackBerry 10, Palm OS, andthe like, and being Internet, e-mail, short message service (SMS),Blackberry®, or other communication protocol enabled. The clientcomputing devices can be general purpose personal computers including,by way of example, personal computers and/or laptop computers runningvarious versions of Microsoft Windows®, Apple Macintosh®, and/or Linuxoperating systems. The client computing devices can be workstationcomputers running any of a variety of commercially-available UNIX® orUNIX-like operating systems, including without limitation the variety ofGNU/Linux operating systems, such as for example, Google Chrome OS.Alternatively, or in addition, client computing devices 102, 104, 106,and 108 may be any other electronic device, such as a thin-clientcomputer, an Internet-enabled gaming system (e.g., a Microsoft Xboxgaming console with or without a Kinect® gesture input device), and/or apersonal messaging device, capable of communicating over network(s) 110.

Although exemplary distributed system 100 is shown with four clientcomputing devices, any number of client computing devices may besupported. Other devices, such as devices with sensors, etc., mayinteract with server 112.

Network(s) 110 in distributed system 100 may be any type of networkfamiliar to those skilled in the art that can support datacommunications using any of a variety of commercially-availableprotocols, including without limitation TCP/IP (transmission controlprotocol/Internet protocol), SNA (systems network architecture), IPX(Internet packet exchange), AppleTalk, and the like. Merely by way ofexample, network(s) 110 can be a local area network (LAN), such as onebased on Ethernet, Token-Ring and/or the like. Network(s) 110 can be awide-area network and the Internet. It can include a virtual network,including without limitation a virtual private network (VPN), anintranet, an extranet, a public switched telephone network (PSTN), aninfra-red network, a wireless network (e.g., a network operating underany of the Institute of Electrical and Electronics (IEEE) 802.11 suiteof protocols, Bluetooth®, and/or any other wireless protocol); and/orany combination of these and/or other networks.

Server 112 may be composed of one or more general purpose computers,specialized server computers (including, by way of example, PC (personalcomputer) servers, UNIX® servers, mid-range servers, mainframecomputers, rack-mounted servers, etc.), server farms, server clusters,or any other appropriate arrangement and/or combination. In variousembodiments, server 112 may be adapted to run one or more services orsoftware applications described in the foregoing disclosure. Forexample, server 112 may correspond to a server for performing processingdescribed above according to an embodiment of the present disclosure.

Server 112 may run an operating system including any of those discussedabove, as well as any commercially available server operating system.Server 112 may also run any of a variety of additional serverapplications and/or mid-tier applications, including HTTP (hypertexttransport protocol) servers, FTP (file transfer protocol) servers, CGI(common gateway interface) servers, JAVA® servers, database servers, andthe like. Exemplary database servers include without limitation thosecommercially available from Oracle, Microsoft, Sybase, IBM(International Business Machines), and the like.

In some implementations, server 112 may include one or more applicationsto analyze and consolidate data feeds and/or event updates received fromusers of client computing devices 102, 104, 106, and 108. As an example,data feeds and/or event updates may include, but are not limited to,Twitter® feeds, Facebook® updates or real-time updates received from oneor more third party information sources and continuous data streams,which may include real-time events related to sensor data applications,financial tickers, network performance measuring tools (e.g., networkmonitoring and traffic management applications), clickstream analysistools, automobile traffic monitoring, and the like. Server 112 may alsoinclude one or more applications to display the data feeds and/orreal-time events via one or more display devices of client computingdevices 102, 104, 106, and 108.

Distributed system 100 may also include one or more databases 114 and116. Databases 114 and 116 may reside in a variety of locations. By wayof example, one or more of databases 114 and 116 may reside on anon-transitory storage medium local to (and/or resident in) server 112.Alternatively, databases 114 and 116 may be remote from server 112 andin communication with server 112 via a network-based or dedicatedconnection. In one set of embodiments, databases 114 and 116 may residein a storage-area network (SAN). Similarly, any necessary files forperforming the functions attributed to server 112 may be stored locallyon server 112 and/or remotely, as appropriate. In one set ofembodiments, databases 114 and 116 may include relational databases,such as databases provided by Oracle, that are adapted to store, update,and retrieve data in response to SQL-formatted commands.

FIG. 2 is a block diagram illustrating components of a systemenvironment by which services provided by embodiments of the presentinvention may be offered as cloud services. In the illustratedembodiment, system environment 200 includes one or more client computingdevices 204, 206, and 208 that may be used by users to interact with acloud infrastructure system 202 that provides cloud services. The clientcomputing devices may be configured to operate a client application suchas a web browser, a proprietary client application (e.g., Oracle Forms),or some other application, which may be used by a user of the clientcomputing device to interact with cloud infrastructure system 202 to useservices provided by cloud infrastructure system 202.

It should be appreciated that cloud infrastructure system 202 depictedin the figure may have other components than those depicted. Further,the embodiment shown in the figure is only one example of a cloudinfrastructure system that may incorporate an embodiment of theinvention. In some other embodiments, cloud infrastructure system 202may have more or fewer components than shown in the figure, may combinetwo or more components, or may have a different configuration orarrangement of components.

Client computing devices 204, 206, and 208 may be devices similar tothose described above for 102, 104, 106, and 108.

Although exemplary system environment 200 is shown with three clientcomputing devices, any number of client computing devices may besupported. Other devices such as devices with sensors, etc. may interactwith cloud infrastructure system 202.

Network(s) 210 may facilitate communications and exchange of databetween clients 204, 206, and 208 and cloud infrastructure system 202.Each network may be any type of network familiar to those skilled in theart that can support data communications using any of a variety ofcommercially-available protocols, including those described above fornetwork(s) 110.

Cloud infrastructure system 202 may comprise one or more computersand/or servers that may include those described above for server 112.

In certain embodiments, services provided by the cloud infrastructuresystem may include a host of services that are made available to usersof the cloud infrastructure system on demand, such as online datastorage and backup solutions, Web-based e-mail services, hosted officesuites and document collaboration services, database processing, managedtechnical support services, and the like. Services provided by the cloudinfrastructure system can dynamically scale to meet the needs of itsusers. A specific instantiation of a service provided by cloudinfrastructure system is referred to herein as a “service instance.” Ingeneral, any service made available to a user via a communicationnetwork, such as the Internet, from a cloud service provider's system isreferred to as a “cloud service.” Typically, in a public cloudenvironment, servers and systems that make up the cloud serviceprovider's system are different from the customer's own on-premisesservers and systems. For example, a cloud service provider's system mayhost an application, and a user may, via a communication network such asthe Internet, on demand, order and use the application.

In some examples, a service in a computer network cloud infrastructuremay include protected computer network access to storage, a hosteddatabase, a hosted web server, a software application, or other serviceprovided by a cloud vendor to a user, or as otherwise known in the art.For example, a service can include password-protected access to remotestorage on the cloud through the Internet. As another example, a servicecan include a web service-based hosted relational database and ascript-language middleware engine for private use by a networkeddeveloper. As another example, a service can include access to an emailsoftware application hosted on a cloud vendor's web site.

In certain embodiments, cloud infrastructure system 202 may include asuite of applications, middleware, and database service offerings thatare delivered to a customer in a self-service, subscription-based,elastically scalable, reliable, highly available, and secure manner. Anexample of such a cloud infrastructure system is the Oracle Public Cloudprovided by the present assignee.

In various embodiments, cloud infrastructure system 202 may be adaptedto automatically provision, manage and track a customer's subscriptionto services offered by cloud infrastructure system 202. Cloudinfrastructure system 202 may provide the cloud services via differentdeployment models. For example, services may be provided under a publiccloud model in which cloud infrastructure system 202 is owned by anorganization selling cloud services (e.g., owned by Oracle) and theservices are made available to the general public or different industryenterprises. As another example, services may be provided under aprivate cloud model in which cloud infrastructure system 202 is operatedsolely for a single organization and may provide services for one ormore entities within the organization. The cloud services may also beprovided under a community cloud model in which cloud infrastructuresystem 202 and the services provided by cloud infrastructure system 202are shared by several organizations in a related community. The cloudservices may also be provided under a hybrid cloud model, which is acombination of two or more different models.

In some embodiments, the services provided by cloud infrastructuresystem 202 may include one or more services provided under Software as aService (SaaS) category, Platform as a Service (PaaS) category,Infrastructure as a Service (IaaS) category, or other categories ofservices including hybrid services. A customer, via a subscriptionmodel, may order one or more services provided by cloud infrastructuresystem 202. Cloud infrastructure system 202 then performs processing toprovide the services in the customer's subscription order.

In some embodiments, the services provided by cloud infrastructuresystem 202 may include, without limitation, application services,platform services and infrastructure services. In some examples,application services may be provided by the cloud infrastructure systemvia a SaaS platform. The SaaS platform may be configured to providecloud services that fall under the SaaS category. For example, the SaaSplatform may provide capabilities to build and deliver a suite ofon-demand applications on an integrated development and deploymentplatform. The SaaS platform may manage and control the underlyingsoftware and infrastructure for providing the SaaS services. Byutilizing the services provided by the SaaS platform, customers canutilize applications executing on the cloud infrastructure system.Customers can acquire the application services without the need forcustomers to purchase separate licenses and support. Any number ofdifferent SaaS services may be provided. Examples include, withoutlimitation, services that provide solutions for sales performancemanagement, enterprise integration, and business flexibility for largeorganizations.

In some embodiments, platform services may be provided by the cloudinfrastructure system via a PaaS platform. The PaaS platform may beconfigured to provide cloud services that fall under the PaaS category.Examples of platform services may include without limitation servicesthat enable organizations (such as Oracle) to consolidate existingapplications on a shared, common architecture, as well as the ability tobuild new applications that leverage the shared services provided by theplatform. The PaaS platform may manage and control the underlyingsoftware and infrastructure for providing the PaaS services. Customerscan acquire the PaaS services provided by the cloud infrastructuresystem without the need for customers to purchase separate licenses andsupport. Examples of platform services include, without limitation,Oracle Java Cloud Service (JCS), Oracle Database Cloud Service (DBCS),and others.

By utilizing the services provided by the PaaS platform, customers canemploy programming languages and tools supported by the cloudinfrastructure system and also control the deployed services. In someembodiments, platform services provided by the cloud infrastructuresystem may include database cloud services, middleware cloud services(e.g., Oracle Fusion Middleware services), and Java cloud services. Inone embodiment, database cloud services may support shared servicedeployment models that enable organizations to pool database resourcesand offer customers a Database as a Service in the form of a databasecloud. Middleware cloud services may provide a platform for customers todevelop and deploy various business applications, and Java cloudservices may provide a platform for customers to deploy Javaapplications, in the cloud infrastructure system.

Various different infrastructure services may be provided by an IaaSplatform in the cloud infrastructure system. The infrastructure servicesfacilitate the management and control of the underlying computingresources, such as storage, networks, and other fundamental computingresources for customers utilizing services provided by the SaaS platformand the PaaS platform.

In certain embodiments, cloud infrastructure system 202 may also includeinfrastructure resources 230 for providing the resources used to providevarious services to customers of the cloud infrastructure system. In oneembodiment, infrastructure resources 230 may include pre-integrated andoptimized combinations of hardware, such as servers, storage, andnetworking resources to execute the services provided by the PaaSplatform and the SaaS platform.

In some embodiments, resources in cloud infrastructure system 202 may beshared by multiple users and dynamically re-allocated per demand.Additionally, resources may be allocated to users in different timezones. For example, cloud infrastructure system 230 may enable a firstset of users in a first time zone to utilize resources of the cloudinfrastructure system for a specified number of hours and then enablethe re-allocation of the same resources to another set of users locatedin a different time zone, thereby maximizing the utilization ofresources.

In certain embodiments, a number of internal shared services 232 may beprovided that are shared by different components or modules of cloudinfrastructure system 202 and by the services provided by cloudinfrastructure system 202. These internal shared services may include,without limitation, a security and identity service, an integrationservice, an enterprise repository service, an enterprise managerservice, a virus scanning and white list service, a high availability,backup and recovery service, service for enabling cloud support, anemail service, a notification service, a file transfer service, and thelike.

In certain embodiments, cloud infrastructure system 202 may providecomprehensive management of cloud services (e.g., SaaS, PaaS, and IaaSservices) in the cloud infrastructure system. In one embodiment, cloudmanagement functionality may include capabilities for provisioning,managing and tracking a customer's subscription received by cloudinfrastructure system 202, and the like.

In one embodiment, as depicted in the figure, cloud managementfunctionality may be provided by one or more modules, such as an ordermanagement module 220, an order orchestration module 222, an orderprovisioning module 224, an order management and monitoring module 226,and an identity management module 228. These modules may include or beprovided using one or more computers and/or servers, which may begeneral purpose computers, specialized server computers, server farms,server clusters, or any other appropriate arrangement and/orcombination.

In exemplary operation 234, a customer using a client device, such asclient device 204, 206 or 208, may interact with cloud infrastructuresystem 202 by requesting one or more services provided by cloudinfrastructure system 202 and placing an order for a subscription forone or more services offered by cloud infrastructure system 202. Incertain embodiments, the customer may access a cloud User Interface(UI), cloud UI 212, cloud UI 214 and/or cloud UI 216 and place asubscription order via these UIs. The order information received bycloud infrastructure system 202 in response to the customer placing anorder may include information identifying the customer and one or moreservices offered by the cloud infrastructure system 202 that thecustomer intends to subscribe to.

After an order has been placed by the customer, the order information isreceived via the cloud UIs, 212, 214 and/or 216.

At operation 236, the order is stored in order database 218. Orderdatabase 218 can be one of several databases operated by cloudinfrastructure system 218 and operated in conjunction with other systemelements.

At operation 238, the order information is forwarded to an ordermanagement module 220. In some instances, order management module 220may be configured to perform billing and accounting functions related tothe order, such as verifying the order, and upon verification, bookingthe order.

At operation 240, information regarding the order is communicated to anorder orchestration module 222. Order orchestration module 222 mayutilize the order information to orchestrate the provisioning ofservices and resources for the order placed by the customer. In someinstances, order orchestration module 222 may orchestrate theprovisioning of resources to support the subscribed services using theservices of order provisioning module 224.

In certain embodiments, order orchestration module 222 enables themanagement of business processes associated with each order and appliesbusiness logic to determine whether an order should proceed toprovisioning. At operation 242, upon receiving an order for a newsubscription, order orchestration module 222 sends a request to orderprovisioning module 224 to allocate resources and configure thoseresources needed to fulfill the subscription order. Order provisioningmodule 224 enables the allocation of resources for the services orderedby the customer. Order provisioning module 224 provides a level ofabstraction between the cloud services provided by cloud infrastructuresystem 200 and the physical implementation layer that is used toprovision the resources for providing the requested services. Orderorchestration module 222 may thus be isolated from implementationdetails, such as whether or not services and resources are actuallyprovisioned on the fly or pre-provisioned and only allocated/assignedupon request.

At operation 244, once the services and resources are provisioned, anotification of the provided service may be sent to customers on clientdevices 204, 206 and/or 208 by order provisioning module 224 of cloudinfrastructure system 202.

At operation 246, the customer's subscription order may be managed andtracked by an order management and monitoring module 226. In someinstances, order management and monitoring module 226 may be configuredto collect usage statistics for the services in the subscription order,such as the amount of storage used, the amount data transferred, thenumber of users, and the amount of system up time and system down time.

In certain embodiments, cloud infrastructure system 200 may include anidentity management module 228. Identity management module 228 may beconfigured to provide identity services, such as access management andauthorization services in cloud infrastructure system 200. In someembodiments, identity management module 228 may control informationabout customers who wish to utilize the services provided by cloudinfrastructure system 202. Such information can include information thatauthenticates the identities of such customers and information thatdescribes which actions those customers are authorized to performrelative to various system resources (e.g., files, directories,applications, communication ports, memory segments, etc.) Identitymanagement module 228 may also include the management of descriptiveinformation about each customer and about how and by whom thatdescriptive information can be accessed and modified.

FIG. 3 is a block diagram illustrating an exemplary computer system inwhich embodiments of the present invention may be implemented. Thesystem 300 may be used to implement any of the computer systemsdescribed above. As shown in the figure, computer system 300 includes aprocessing unit 304 that communicates with a number of peripheralsubsystems via a bus subsystem 302. These peripheral subsystems mayinclude a processing acceleration unit 306, an I/O subsystem 308, astorage subsystem 318 and a communications subsystem 324. Storagesubsystem 318 includes tangible computer-readable storage media 322 anda system memory 310.

Bus subsystem 302 provides a mechanism for letting the variouscomponents and subsystems of computer system 300 communicate with eachother as intended. Although bus subsystem 302 is shown schematically asa single bus, alternative embodiments of the bus subsystem may utilizemultiple buses. Bus subsystem 302 may be any of several types of busstructures including a memory bus or memory controller, a peripheralbus, and a local bus using any of a variety of bus architectures. Forexample, such architectures may include an Industry StandardArchitecture (ISA) bus, Micro Channel Architecture (MCA) bus, EnhancedISA (EISA) bus, Video Electronics Standards Association (VESA) localbus, and Peripheral Component Interconnect (PCI) bus, which can beimplemented as a Mezzanine bus manufactured to the IEEE P1386.1standard.

Processing unit 304, which can be implemented as one or more integratedcircuits (e.g., a conventional microprocessor or microcontroller),controls the operation of computer system 300. One or more processorsmay be included in processing unit 304. These processors may includesingle core or multicore processors. In certain embodiments, processingunit 304 may be implemented as one or more independent processing units332 and/or 334 with single or multicore processors included in eachprocessing unit. In other embodiments, processing unit 304 may also beimplemented as a quad-core processing unit formed by integrating twodual-core processors into a single chip.

In various embodiments, processing unit 304 can execute a variety ofprograms in response to program code and can maintain multipleconcurrently executing programs or processes. At any given time, some orall of the program code to be executed can be resident in processor(s)304 and/or in storage subsystem 318. Through suitable programming,processor(s) 304 can provide various functionalities described above.Computer system 300 may additionally include a processing accelerationunit 306, which can include a digital signal processor (DSP), aspecial-purpose processor, and/or the like.

I/O subsystem 308 may include user interface input devices and userinterface output devices. User interface input devices may include akeyboard, pointing devices such as a mouse or trackball, a touchpad ortouch screen incorporated into a display, a scroll wheel, a click wheel,a dial, a button, a switch, a keypad, audio input devices with voicecommand recognition systems, microphones, and other types of inputdevices. User interface input devices may include, for example, motionsensing and/or gesture recognition devices such as the Microsoft Kinect®motion sensor that enables users to control and interact with an inputdevice, such as the Microsoft Xbox® 360 game controller, through anatural user interface using gestures and spoken commands. Userinterface input devices may also include eye gesture recognition devicessuch as the Google Glass® blink detector that detects eye activity(e.g., ‘blinking’ while taking pictures and/or making a menu selection)from users and transforms the eye gestures as input into an input device(e.g., Google Glass®). Additionally, user interface input devices mayinclude voice recognition sensing devices that enable users to interactwith voice recognition systems (e.g., Siri® navigator), through voicecommands.

User interface input devices may also include, without limitation, threedimensional (3D) mice, joysticks or pointing sticks, gamepads andgraphic tablets, and audio/visual devices such as speakers, digitalcameras, digital camcorders, portable media players, webcams, imagescanners, fingerprint scanners, barcode reader 3D scanners, 3D printers,laser rangefinders, and eye gaze tracking devices. Additionally, userinterface input devices may include, for example, medical imaging inputdevices such as computed tomography, magnetic resonance imaging,position emission tomography, medical ultrasonography devices. Userinterface input devices may also include, for example, audio inputdevices such as MIDI keyboards, digital musical instruments and thelike.

User interface output devices may include a display subsystem, indicatorlights, or non-visual displays such as audio output devices, etc. Thedisplay subsystem may be a cathode ray tube (CRT), a flat-panel device,such as that using a liquid crystal display (LCD) or plasma display, aprojection device, a touch screen, and the like. In general, use of theterm “output device” is intended to include all possible types ofdevices and mechanisms for outputting information from computer system300 to a user or other computer. For example, user interface outputdevices may include, without limitation, a variety of display devicesthat visually convey text, graphics and audio/video information such asmonitors, printers, speakers, headphones, automotive navigation systems,plotters, voice output devices, and modems.

Computer system 300 may comprise a storage subsystem 318 that comprisessoftware elements, shown as being currently located within a systemmemory 310. System memory 310 may store program instructions that areloadable and executable on processing unit 304, as well as datagenerated during the execution of these programs.

Depending on the configuration and type of computer system 300, systemmemory 310 may be volatile (such as random access memory (RAM)) and/ornon-volatile (such as read-only memory (ROM), flash memory, etc.) TheRAM typically contains data and/or program modules that are immediatelyaccessible to and/or presently being operated and executed by processingunit 304. In some implementations, system memory 310 may includemultiple different types of memory, such as static random access memory(SRAM) or dynamic random access memory (DRAM). In some implementations,a basic input/output system (BIOS), containing the basic routines thathelp to transfer information between elements within computer system300, such as during start-up, may typically be stored in the ROM. By wayof example, and not limitation, system memory 310 also illustratesapplication programs 312, which may include client applications, Webbrowsers, mid-tier applications, relational database management systems(RDBMS), etc., program data 314, and an operating system 316. By way ofexample, operating system 316 may include various versions of MicrosoftWindows®, Apple Macintosh®, and/or Linux operating systems, a variety ofcommercially-available UNIX® or UNIX-like operating systems (includingwithout limitation the variety of GNU/Linux operating systems, theGoogle Chrome® OS, and the like) and/or mobile operating systems such asiOS, Windows® Phone, Android® OS, BlackBerry® 10 OS, and Palm® OSoperating systems.

Storage subsystem 318 may also provide a tangible computer-readablestorage medium for storing the basic programming and data constructsthat provide the functionality of some embodiments. Software (programs,code modules, instructions) that when executed by a processor providethe functionality described above may be stored in storage subsystem318. These software modules or instructions may be executed byprocessing unit 304. Storage subsystem 318 may also provide a repositoryfor storing data used in accordance with the present invention.

Storage subsystem 300 may also include a computer-readable storage mediareader 320 that can further be connected to computer-readable storagemedia 322. Together and, optionally, in combination with system memory310, computer-readable storage media 322 may comprehensively representremote, local, fixed, and/or removable storage devices plus storagemedia for temporarily and/or more permanently containing, storing,transmitting, and retrieving computer-readable information.

Computer-readable storage media 322 containing code, or portions ofcode, can also include any appropriate media known or used in the art,including storage media and communication media, such as but not limitedto, volatile and non-volatile, removable and non-removable mediaimplemented in any method or technology for storage and/or transmissionof information. This can include tangible computer-readable storagemedia such as RAM, ROM, electronically erasable programmable ROM(EEPROM), flash memory or other memory technology, CD-ROM, digitalversatile disk (DVD), or other optical storage, magnetic cassettes,magnetic tape, magnetic disk storage or other magnetic storage devices,or other tangible computer readable media. This can also includenontangible computer-readable media, such as data signals, datatransmissions, or any other medium which can be used to transmit thedesired information and which can be accessed by computing system 300.

By way of example, computer-readable storage media 322 may include ahard disk drive that reads from or writes to non-removable, nonvolatilemagnetic media, a magnetic disk drive that reads from or writes to aremovable, nonvolatile magnetic disk, and an optical disk drive thatreads from or writes to a removable, nonvolatile optical disk such as aCD ROM, DVD, and Blu-Ray® disk, or other optical media.Computer-readable storage media 322 may include, but is not limited to,Zip® drives, flash memory cards, universal serial bus (USB) flashdrives, secure digital (SD) cards, DVD disks, digital video tape, andthe like. Computer-readable storage media 322 may also include,solid-state drives (SSD) based on non-volatile memory such asflash-memory based SSDs, enterprise flash drives, solid state ROM, andthe like, SSDs based on volatile memory such as solid state RAM, dynamicRAM, static RAM, DRAM-based SSDs, magnetoresistive RAM (MRAM) SSDs, andhybrid SSDs that use a combination of DRAM and flash memory based SSDs.The disk drives and their associated computer-readable media may providenon-volatile storage of computer-readable instructions, data structures,program modules, and other data for computer system 300.

Communications subsystem 324 provides an interface to other computersystems and networks. Communications subsystem 324 serves as aninterface for receiving data from and transmitting data to other systemsfrom computer system 300. For example, communications subsystem 324 mayenable computer system 300 to connect to one or more devices via theInternet. In some embodiments communications subsystem 324 can includeradio frequency (RF) transceiver components for accessing wireless voiceand/or data networks (e.g., using cellular telephone technology,advanced data network technology, such as 3G, 4G or EDGE (enhanced datarates for global evolution), WiFi (IEEE 802.11 family standards, orother mobile communication technologies, or any combination thereof),global positioning system (GPS) receiver components, and/or othercomponents. In some embodiments communications subsystem 324 can providewired network connectivity (e.g., Ethernet) in addition to or instead ofa wireless interface.

In some embodiments, communications subsystem 324 may also receive inputcommunication in the form of structured and/or unstructured data feeds326, event streams 328, event updates 330, and the like on behalf of oneor more users who may use computer system 300.

By way of example, communications subsystem 324 may be configured toreceive data feeds 326 in real-time from users of social networks and/orother communication services such as Twitter® feeds, Facebook® updates,web feeds such as Rich Site Summary (RSS) feeds, and/or real-timeupdates from one or more third party information sources.

Additionally, communications subsystem 324 may also be configured toreceive data in the form of continuous data streams, which may includeevent streams 328 of real-time events and/or event updates 330, that maybe continuous or unbounded in nature with no explicit end. Examples ofapplications that generate continuous data may include, for example,sensor data applications, financial tickers, network performancemeasuring tools (e.g. network monitoring and traffic managementapplications), clickstream analysis tools, automobile trafficmonitoring, and the like.

Communications subsystem 324 may also be configured to output thestructured and/or unstructured data feeds 326, event streams 328, eventupdates 330, and the like to one or more databases that may be incommunication with one or more streaming data source computers coupledto computer system 300.

Computer system 300 can be one of various types, including a handheldportable device (e.g., an iPhone® cellular phone, an iPad® computingtablet, a PDA), a wearable device (e.g., a Google Glass® head mounteddisplay), a PC, a workstation, a mainframe, a kiosk, a server rack, orany other data processing system.

Due to the ever-changing nature of computers and networks, thedescription of computer system 300 depicted in the figure is intendedonly as a specific example. Many other configurations having more orfewer components than the system depicted in the figure are possible.For example, customized hardware might also be used and/or particularelements might be implemented in hardware, firmware, software (includingapplets), or a combination. Further, connection to other computingdevices, such as network input/output devices, may be employed. Based onthe disclosure and teachings provided herein, a person of ordinary skillin the art will appreciate other ways and/or methods to implement thevarious embodiments.

As introduced above, embodiments of the invention provide systems andmethods for logging of messages in a development or other environment.More specifically, embodiments of the present invention providedynamically adaptive logging of runtime messages generated by anapplication such as an application under test in the developmentenvironment. These embodiments provide a way to handle the volume ofinformation stored in the logs by dynamically changing the severityassociated with generated messages based on previous code pathexecution. Additionally or alternatively, embodiments can use a set ofmetrics to replace the usual static log level associated with the codeby the developer. For example, such metrics can include but are notlimited to a cost-based (storage volume on disk), an exception-based(weight increase in catch block), and/or a crowd-based (community canvote down noise). As a result, embodiments can provide more detailedinformation when the error is recurring for a particular user butwithout generating so much information as to make the log difficult touse. It should be noted that while described herein as being implementedin a development environment, embodiments of the present invention arethought to be equally applicable to other runtime environments and othersituations in which an application generates or causes the generation oflog messages. These various different implementations are alsoconsidered to be within the scope of the present invention.

FIG. 4 is a block diagram illustrating, at a high-level, functionalcomponents of a system for providing dynamically adaptive logging ofruntime messages generated by an application according to one embodimentof the present invention. As illustrated in this example, the system 400can include a development or other runtime environment 405 which can beimplemented on any of the servers or other computers described above. Anapplication 410 can be executed in this runtime environment 405. Forexample, if the runtime environment 405 comprises or is part of adevelopment environment or system, the application 410 can comprise anapplication undergoing testing or debugging. The system 400 can alsoinclude a logging framework 415. For example, the logging framework 415can comprise the Java logging framework or other similar framework forlogging messages generated during and based on execution of theapplication 410. For example, the application 410 can log a message bypassing an object or an exception to the logging framework 415 throughan Application Program Interface (API) (not shown here) of the loggingframework 415. A logger 420 of the framework 415 can record messageassociated with the object or exception in one or more logs 435.

According to one embodiment, the logger 420 can perform dynamicallyadaptive logging of the runtime messages generated by or based onexecution of the application 410. Generally speaking, the logger 420 canadaptively log runtime messages related to the application 410 in one ormore logs 435 by detecting a predefined condition of the application410, such as an exception, and determining an execution state of theapplication 410 at a time the predefined condition is detected. Forexample, determining an execution state of the application 410 caninclude determining a current execution path within the application 410.According to one embodiment, detecting the condition or exception anddetermining the execution state of the application 410 can be performed,for example, through the API of the logging framework 415. For example,the logger 420 can receive objects related to or indicating theconditions or exceptions from the application 405 and can providemethods for determining a current state of the application 410.Additionally or alternatively, the application can periodically or uponoccurrence of certain conditions or exceptions provide current stateand/or execution path information to the logger 420 through the API ofthe logging framework 415. A dynamic determination can then be made bythe logger 420 as to whether to generate a log message associated withthe detected predefined condition or to suppress generation of the logmessage associated with the detected predefined condition based at leastin part on the determined execution state at the time the predefinedcondition is detected.

More specifically, the logger 420 can dynamically determine whether togenerate a log message associated with the detected predefined conditionof the application 410 or to suppress generation of the log message bydetermining whether the predefined condition or exception has previouslyoccurred. In response to determining the predefined condition has notpreviously occurred, the logger 420 can suppress generation of the logmessage associated with the detected predefined condition but can save arecord 425 of the detected predefined condition and the determinedexecution state of the application at a time the predefined condition isdetected. In addition, the logger can weigh the detected predefinedcondition. Weighting of the condition or exception can comprise, forexample, incrementing or increasing a severity level associated withthat condition of exception.

In response to determining the predefined condition has been previouslydetected, the logger 420 can make a determination based on a set of oneor more metrics 430 as to whether to generate a log message associatedwith the detected predefined condition or to suppress generation of thelog message. For example, the metrics 430 can comprise one or morecost-based metrics such as used and/or required storage volume forstoring the generated message(s). Other cost based metrics might includerequired processor overhead and/or current processor load, expected timeto handle and record a particular log message etc. Making determinationsbased on these metrics might also consider a current level of thedetected exception or weight of the detected condition. In anotherexample, the metrics can additionally or alternatively include one ormore exception-based metrics related to the weight of the condition orexception. Such metrics might define a minimum severity level to berecorded etc. In yet another example, the metrics can additionally oralternatively include one or more crowd-based metrics generated based oninput from a set of user and in which this community of user can vote upor down particular conditions or exceptions. For example, a group ofdevelopers might indicate a particular interest or disinterest in acertain execution state or path and/or certain conditions/exceptions. Insuch cases, the suppression or generation of the corresponding messagesmay be based on these factors relative to a severity level of thedetected exception or weight of the detected condition It should beunderstood that other metrics are contemplated and considered to bewithin the scope of the present invention.

In response to determining to suppress generation of the log messageassociated with the detected predefined condition based on a set of oneor more metrics, the logger 420 can suppress generation of the logmessage but can increase the weight of the detected predefined conditionor exception, e.g., the exception level can be increased but withoutgenerating and storing the corresponding message in the logs 435. Inresponse to determining to generate the log message associated with thedetected predefined condition based on a set of one or more metrics, thelogger 420 can increase the weight of the detected predefined conditionand generate the log message associated with the detected predefinedcondition to be stored or recorded in the logs 435. The logger can thenmake a determination as to whether to continue adaptively loggingruntime messages associated with the detected and logged predefinedcondition or exception of the application. For example, thisdetermination may be made based on a maximum weight or exception levelbeing reached, based on a preset maximum number of messages beinglogged, either over all or for this particular condition/exception alongthis execution path or for this execution state, or based on otherfactors or conditions. Additionally or alternatively, this determinationcan be made based on a time-based series of events and/or a phase of thesystem, e.g., a startup phase or shutdown phase that can be tied to orrelated to specific patterns in the logs. In response to determining tonot continue adaptively logging runtime messages associated with thedetected predefined condition for the application, the logger 420 canhalt or suspend further logging of messages associated with the detectedpredefined condition or exception and for the determined execution stateof the application 410. In other words, once the weight of the conditionor exception has reached a certain point, or a certain number ofmessages have already been recorded, etc., further logging of presumablyrepetitive messages can be prevented by no longer logging messages forthe same condition/exception occurring on the same state or executionpath.

FIG. 5 is a flowchart illustrating a process for providing dynamicallyadaptive logging of runtime messages generated by an applicationaccording to one embodiment of the present invention. As illustrated inthis example, adaptively logging runtime messages related to anapplication can comprise detecting 505 a predefined condition of theapplication, such as an exception, and determining 510 an executionstate of the application at a time the predefined condition is detected.For example, determining 510 an execution state of the application caninclude determining a current execution path within the application. Adynamic determination can then be made 515-550 as to whether to generatea log message associated with the detected predefined condition or tosuppress generation of the log message associated with the detectedpredefined condition based at least in part on the determined executionstate at the time the predefined condition is detected.

More specifically, dynamically determining whether to generate a logmessage associated with the detected predefined condition or to suppressgeneration of the log message associated with the detected predefinedcondition can comprise determining 515 whether the predefined conditionhas been previously detected. In response to determining 515 thepredefined condition has not been previously detected, i.e., this is thefirst occurrence of the condition or exception, generation of the logmessage associated with the detected predefined condition can besuppressed but, the detected predefined condition and the determinedexecution state of the application at a time the predefined condition isdetected can be saved 520 and the detected predefined condition can beweighted 530. Weighting 530 of the condition or exception can comprise,for example, incrementing or increasing a severity level associated withthat condition of exception.

In response to determining 515 the predefined condition has beenpreviously detected, a determination 525 can be made based on a set ofone or more metrics as to whether to generate a log message associatedwith the detected predefined condition or to suppress generation of thelog message associated with the detected predefined condition. Forexample, the metrics can comprise one or more cost-based metrics such asused and/or required storage volume for storing the generatedmessage(s). In another example, the metrics can additionally oralternatively include one or more exception-based metrics related to theweight of the condition or exception. In yet another example, themetrics can additionally or alternatively include one or morecrowd-based metrics generated based on input from a set of user and inwhich this community of user can vote up or down particular conditionsor exceptions.

In response to determining 525 to suppress generation of the log messageassociated with the detected predefined condition based on a set of oneor more metrics, generation of the log message associated with thedetected predefined condition can be suppressed but, the weight of thedetected predefined condition or exception can be increased 530, e.g.,the exception level can be increased. In response to determining 525 togenerate the log message associated with the detected predefinedcondition based on a set of one or more metrics, the weight of thedetected predefined condition can be increased 535, e.g., the exceptionlevel can be increased, and the log message associated with the detectedpredefined condition can be generated 540. A determination 545 may thenbe made as to whether to continue adaptively logging runtime messagesassociated with the detected 505 and logged 540 predefined condition orexception of the application. For example, this determination 545 may bemade based on a maximum weight or exception level being reached, basedon a preset maximum number of messages being logged, either over all orfor this particular condition/exception along this execution path or forthis execution state, or based on other factors or conditions. Inresponse to determining 545 to not continue adaptively logging runtimemessages associated with the detected predefined condition for theapplication, further logging of messages associated with the detectedpredefined condition or exception and for the determined execution stateof the application can be halted 550.

In the foregoing description, for the purposes of illustration, methodswere described in a particular order. It should be appreciated that inalternate embodiments, the methods may be performed in a different orderthan that described. It should also be appreciated that the methodsdescribed above may be performed by hardware components or may beembodied in sequences of machine-executable instructions, which may beused to cause a machine, such as a general-purpose or special-purposeprocessor or logic circuits programmed with the instructions to performthe methods. These machine-executable instructions may be stored on oneor more machine readable mediums or memory devices, such as CD-ROMs orother type of optical disks, floppy diskettes, ROMs, RAMs, EPROMs,EEPROMs, magnetic or optical cards, flash memory, or other types ofmachine-readable mediums or memory devices suitable for storingelectronic instructions. Alternatively, the methods may be performed bya combination of hardware and software.

While illustrative and presently preferred embodiments of the inventionhave been described in detail herein, it is to be understood that theinventive concepts may be otherwise variously embodied and employed, andthat the appended claims are intended to be construed to include suchvariations, except as limited by the prior art.

What is claimed is:
 1. A method for adaptively logging runtime messagesrelated to an application, the method comprising: detecting a predefinedcondition of the application; determining an execution state of theapplication at a time the predefined condition is detected; anddynamically determining whether to generate a log message associatedwith the detected predefined condition or to suppress generation of thelog message associated with the detected predefined condition, whereindynamically determining whether to generate the log message associatedwith the detected predefined condition or to suppress generation of thelog message associated with the detected predefined condition includes:determining whether the predefined condition of the application has beenpreviously detected; and in response to determining the predefinedcondition has not been previously detected, suppressing generation ofthe log message associated with the detected predefined condition,saving the detected predefined condition and the determined executionstate of the application at the time the predefined condition isdetected, and weighting the detected predefined condition.
 2. The methodof claim 1, wherein dynamically determining whether to generate the logmessage associated with the detected predefined condition or to suppressgeneration of the log message associated with the detected predefinedcondition further comprises, in response to determining the predefinedcondition has been previously detected: determining based on a set ofone or more metrics whether to generate the log message associated withthe detected predefined condition or to suppress generation of the logmessage associated with the detected predefined condition; in responseto determining to suppress generation of the log message associated withthe detected predefined condition based on the set of one or moremetrics, suppressing generation of the log message associated with thedetected predefined condition and increasing the weighting of thedetected predefined condition; and in response to determining togenerate the log message associated with the detected predefinedcondition based on the set of one or more metrics, increasing theweighting of the detected predefined condition and generating the logmessage associated with the detected predefined condition.
 3. The methodof claim 2, wherein the metrics comprise one or more cost-based metrics.4. The method of claim 2, wherein the metrics comprise one or moreexception-based metrics.
 5. The method of claim 2, wherein the metricscomprise one or more crowd-based metrics.
 6. The method of claim 2,further comprising determining whether to continue adaptively loggingruntime messages associated with the detected predefined condition ofthe application.
 7. The method of claim 6, further comprising, inresponse to determining to not continue adaptively logging runtimemessages associated with the detected predefined condition for theapplication, halting logging of messages associated with the detectedpredefined condition for the determined execution state of theapplication.
 8. A system comprising: a processor; and a memory coupledwith and readable by the processor and storing therein a set ofinstructions which, when executed by the processor, causes the processorto adaptively log runtime messages related to an application by:detecting a predefined condition of the application; determining anexecution state of the application at a time the predefined condition isdetected; and dynamically determining whether to generate a log messageassociated with the detected predefined condition or to suppressgeneration of the log message associated with the detected predefinedcondition, wherein dynamically determining whether to generate the logmessage associated with the detected predefined condition or to suppressgeneration of the log message associated with the detected predefinedcondition includes: determining whether the predefined condition of theapplication has been previously detected; and in response to determiningthe predefined condition has not been previously detected, suppressinggeneration of the log message associated with the detected predefinedcondition, saving the detected predefined condition and the determinedexecution state of the application at the time the predefined conditionis detected, and weighting the detected predefined condition.
 9. Thesystem of claim 8, wherein dynamically determining whether to generatethe log message associated with the detected predefined condition or tosuppress generation of the log message associated with the detectedpredefined condition further comprises, in response to determining thepredefined condition has been previously detected: determining based ona set of one or more metrics whether to generate the log messageassociated with the detected predefined condition or to suppressgeneration of the log message associated with the detected predefinedcondition; in response to determining to suppress generation of the logmessage associated with the detected predefined condition based on theset of one or more metrics, suppressing generation of the log messageassociated with the detected predefined condition and increasing theweighting of the detected predefined condition; and in response todetermining to generate the log message associated with the detectedpredefined condition based on the set of one or more metrics, increasingthe weighting of the detected predefined condition and generating thelog message associated with the detected predefined condition.
 10. Thesystem of claim 9, wherein the metrics comprise one or more cost-basedmetrics.
 11. The system of claim 9, wherein the metrics comprise one ormore exception-based metrics.
 12. The system of claim 9, wherein themetrics comprise one or more crowd-based metrics.
 13. The system ofclaim 9, further comprising determining whether to continue adaptivelylogging runtime messages associated with the detected predefinedcondition of the application.
 14. The system of claim 13, furthercomprising, in response to determining to not continue adaptivelylogging runtime messages associated with the detected predefinedcondition for the application, halting logging of messages associatedwith the detected predefined condition for the determined executionstate of the application.
 15. A computer-readable memory comprising aset of instructions stored therein which, when executed by a processor,causes the processor to adaptively log runtime messages related to anapplication by: detecting a predefined condition of the application;determining an execution state of the application at a time thepredefined condition is detected; and dynamically determining whether togenerate a log message associated with the detected predefined conditionor to suppress generation of the log message associated with thedetected predefined condition, wherein dynamically determining whetherto generate the log message associated with the detected predefinedcondition or to suppress generation of the log message associated withthe detected predefined condition includes: determining whether thepredefined condition of the application has been previously detected;and in response to determining the predefined condition has not beenpreviously detected, suppressing generation of the log messageassociated with the detected predefined condition, saving the detectedpredefined condition and the determined execution state of theapplication at the time the predefined condition is detected, andweighting the detected predefined condition.
 16. The computer-readablememory of claim 15, wherein dynamically determining whether to generatethe log message associated with the detected predefined condition or tosuppress generation of the log message associated with the detectedpredefined condition further comprises, in response to determining thepredefined condition has been previously detected: determining based ona set of one or more metrics whether to generate the log messageassociated with the detected predefined condition or to suppressgeneration of the log message associated with the detected predefinedcondition; in response to determining to suppress generation of the logmessage associated with the detected predefined condition based on theset of one or more metrics, suppressing generation of the log messageassociated with the detected predefined condition and increasing theweighting of the detected predefined condition; and in response todetermining to generate the log message associated with the detectedpredefined condition based on the set of one or more metrics, increasingthe weighting of the detected predefined condition and generating thelog message associated with the detected predefined condition.
 17. Thecomputer-readable memory of claim 16, further comprising determiningwhether to continue adaptively logging runtime messages associated withthe detected predefined condition of the application and in response todetermining to not continue adaptively logging runtime messagesassociated with the detected predefined condition for the application,halting logging of messages associated with the detected predefinedcondition for the determined execution state of the application.
 18. Amethod for adaptively logging runtime messages related to anapplication, the method comprising: detecting a predefined condition ofthe application; determining an execution state of the application at atime the predefined condition is detected; and dynamically determiningwhether to generate a log message associated with the detectedpredefined condition or to suppress generation of the log messageassociated with the detected predefined condition, wherein dynamicallydetermining whether to generate the log message associated with thedetected predefined condition or to suppress generation of the logmessage associated with the detected predefined condition includes:determining whether the predefined condition of the application has beenpreviously detected; and in response to determining the predefinedcondition has been previously detected: determining based on a set ofone or more metrics whether to generate the log message associated withthe detected predefined condition or to suppress generation of the logmessage associated with the detected predefined condition; in responseto determining to suppress generation of the log message associated withthe detected predefined condition based on the set of one or moremetrics, suppressing generation of the log message associated with thedetected predefined condition and increasing a weight of the detectedpredefined condition; and in response to determining to generate the logmessage associated with the detected predefined condition based on theset of one or more metrics, increasing the weight of the detectedpredefined condition and generating the log message associated with thedetected predefined condition.
 19. The method of claim 18, wherein themetrics comprise one or more cost-based metrics, exception-basedmetrics, or crowd-based metrics.
 20. The method of claim 18, furthercomprising: in response to determining the predefined condition has notbeen previously detected, suppressing generation of the log messageassociated with the detected predefined condition, saving the detectedpredefined condition and the determined execution state of theapplication at the time the predefined condition is detected, anddetermining the weight of the detected predefined condition.